# . Is this multiple regression model better than the linear model that we generated in parts 110? Explain.

Project Part B: Hypothesis Testing and Confidence IntervalsYour manager has speculated the following.a. The average (mean) annual income was greater than $45,000.b. The true population proportion of customers who live in a suburban area is less than 45%.c. The average (mean) number of years lived in the current home is greater than 8 years.d. The average (mean) credit balance for rural customers is less than $3,200.Using the sample data, perform the hypothesis test for each of the above situations in order to see if there is evidence to support your managers belief in each case AD. In each case, use the Seven Elements of a Test of Hypothesis in Section 6.2 of your text book with = .05, and explain your conclusion in simple terms. Also, be sure to compute the p-value and interpret.Follow this up with computing 95% confidence intervals for each of the variables described in AD, and again interpreting these intervals.Write a report to your manager about the results, distilling down the results in a way that would be understandable to someone who does not know statistics. Clear explanations and interpretations are critical.All DeVry University policies are in effect, including the plagiarism policy.Project Part B report is due by the end of Week 6.Project Part B is worth 100 total points. See the grading rubric below.Submission: The report from Part 3 and all of the relevant work done in the hypothesis testing (including minitab) in 1 and the confidence intervals (minitab) in Part 2 as an appendixFormat for report:Summary report (about one paragraph on each of the speculations, AD)Appendix with all of the steps in hypothesis testing (the format of the Seven Elements of a Test of Hypothesis, in Section 6.2 of your text book) for each speculation AD, as well as the confidence intervals, including all minitab outputPart C:Project Part C: Regression and Correlation AnalysisUsing MINITAB, perform the regression and correlation analysis for the data on income(Y), the dependent variable, and credit balance (X), the independent variable, by answering the following.1. Generate a scatterplot for income ($1,000) versus credit balance($), including the graph of the best fit line. Interpret.2. Determine the equation of the best fit line, which describes the relationship between income and credit balance.3. Determine the coefficient of correlation. Interpret.4. Determine the coefficient of determination. Interpret.5. Test the utility of this regression model (use a two tail test with =.05). Interpret your results, including the p-value.6. Based on your findings in 15, what is your opinion about using credit balance to predict income? Explain.7. Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval.8. Using an interval, estimate the average income for customers that have credit balance of $4,000. Interpret this interval.9. Using an interval, predict the income for a customer that has a credit balance of $4,000. Interpret this interval.10. What can we say about the income for a customer that has a credit balance of $10,000? Explain your answer.In an attempt to improve the model, we attempt to do a multiple regression model predicting income based on credit balance, years, and size.11. Using MINITAB, run the multiple regression analysis using the variables credit balance, years, and size to predict income. State the equation for this multiple regression model.12. Perform the global test foruUtility (F-Test). Explain your conclusion.13. Perform the t-test on each independent variable. Explain your conclusions and clearly state how you should proceed. In particular, state which independent variables should we keep and which should be discarded.14. Is this multiple regression model better than the linear model that we generated in parts 110? Explain.All DeVry University policies are in effect, including the plagiarism policy.15. Project Part C report is due by the end of Week 7.16. Project Part C is worth 100 total points. See the grading rubric below.Summarize your results from 114 in a report that is 3 pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.